• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.6 no.1_2
• /
• pp.44-48
• /
• 1973

Since no medium-sized anchovies for skipjack baits are caught during the winter season in the Korean waters, the demand for the live baits in the winter season is met with crawl-stocked anchovies. Authors conducted a test on the wintering of the anchovies which were caught in the early November and acclimated for 22days in a crawl. The wintering crawl was kept in the inlet near Chungmu City, which is situated in the southern coast of Korea, for 4 months through December 1, 1971 to March 31, 1972. 1. The lowest water temperature of $7.2^{\circ}C$ recorded on March 1, caused no significant mortality of the wintering anchovies. However, two operations, moving the crawl and repacling the crawl webbing, brought about a considerable mortality. The mortality of the anchovies, due to the crawl moving to the wintering place two kilometers away from the transient acclimating place, amounted to 1.5 percent in 9 days following the crawl moving. The replacement of the fouled crawl webbing with a new one also caused a mortality amounting to 1.7 percent in 5 days. 2. It is judged that the favorable wintering waters lie in the south and southeast coasts of Keoje Island, the south and southwest coast of Chungmu City, coasts around Namhae Island, and the east coast of Dolsan Island. Jinhae Bay is not suited for the wintering because of its low water temperature in winter 3. The wintering anchovies wvere fed, once a day through the test period, with 4 kg of finely minced fresh anchovy for 57days in the early period, and with 2kg of compound pellet fish food for the rest of the period. Fatness coefficient of the wintering anchovies showed a slight increase in the latter half of the period.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.11
• /
• pp.1082-1091
• /
• 2007

In this paper, we developed a new hybrid mobile robot which can climb stairs and go over thresholds by crawl gait with embedded real-time control software. This robot is also categorized into hybrid robot that has advantages of wheeled mobile robot and legged mobile robot, but adopts gait feature of crocodile named belly crawl. We imitated the belly crawl using four legs of 2 DOF, four omni-directional wheels, and embedded control software which controls legs and wheels. This software is developed using RTAI/Linux, real-time drivers. As a result, the new hybrid mobile robot has crawl gait. Using this feature, the new hybrid mobile robot can climb stairs and go over thresholds just by path planning of each leg with size of stairs and thresholds, and computing the movement distance of robot body center without considering stability. The performance of our new hybrid mobile robot is verified via experiments.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06c
• /
• pp.118-121
• /
• 2010

The dynamic nature and exponential growth of the World Wide Web remain crawling important pages early still challenging. State-of-the-art crawl scheduling algorithms require huge running time to prioritize web pages during crawling. In this research, we proposed crawl scheduling algorithms that are not only fast but also download important pages early. The algorithms give high importance to some specific pages those have good linkages such as inlinks from different domains or host. The proposed algorithms were experimented on publically available large datasets. The results of experiments showed that propagating more importance to the inter-host links improves the effectiveness of crawl scheduling than the current state-of-the-art crawl scheduling algorithms.

• Journal of Digital Contents Society
• /
• v.4 no.2
• /
• pp.127-137
• /
• 2003

A Web crawler is an important Internet software technology used in a variety of Internet application software which includes search engines. As Internet continues to grow, implementations of high performance web crawlers are urgently demanded. In this paper, we study how to support dynamic scheduling for a multiprocess-based web crawler. For high performance, web crawlers are usually based on multiprocess in their implementations. In these systems, crawl scheduling which manages the allocation of web pages to each process for loading is one of the important issues. In this paper, we identify issues which are important and challenging in the crawl scheduling. To address the issue, we propose a dynamic crawl scheduling framework and subsequently a system architecture for a web crawler with dynamic crawl scheduling support. This paper presents the design of the Web crawler with dynamic scheduling support.

• Journal of Korea Society of Industrial Information Systems
• /
• v.8 no.4
• /
• pp.64-72
• /
• 2003

A Web crawler is an important Internet software technology used in a variety of Internet application software which includes search engines. As Internet continues to grow, implementations of high performance web crawlers are urgently demanded. In this paper, we study how to support dynamic scheduling for a multiprocess-based web crawler. For high peformance, web crawlers are usually based on multiprocess in their implementations. In these systems, crawl scheduling which manages the allocation of web pages to each process for loading is one of the important issues. In this paper, we identify issues which are important and challenging in the crawl scheduling. To address the issue, we propose a dynamic crawl scheduling framework and subsequently a system architecture for a web crawler with dynamic crawl scheduling support. And we analysed the behaviors of Web crawler. Based on the analysis result, we suggest the direction for the design of high performance Web crawler.

• Journal of Korea Society of Industrial Information Systems
• /
• v.8 no.3
• /
• pp.12-18
• /
• 2003

A web crawler is used widely in a variety of Internet applications such as search engines. As the Internet continues to grow, high performance web crawlers become more essential. Crawl scheduling which manages the allocation of web pages to each process for downloading documents is one of the important issues. In this paper, we identify issues that are important and challenging in the crawl scheduling. To address the issues, we propose a dynamic owl scheduling framework and subsequently a system architecture for a web crawler subject to the framework. This paper presents the architecture of a web crawler with dynamic scheduling support. The result of our preliminary performance evaluation made to the proposed crawler architecture is also presented.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.7-10
• /
• 2000

Inadequate footholds selection may result in deadlock state where the walking vehicle can not anymore to the desired direction. This paper concerns about the footholds selection for quadruped v, vehicle to walk with the leg lifting sequence of crawl gait which is desired for straight motion. supporting states for lifting a leg are defined and the proper supporting condition for quadruped c: also proposed. When selecting a footholds of swing leg within the proposed footholds searching are; supporting states after the swing legs are placed, satisfy the proper supporting condition. So it can I for quadruped to execute continuous walking with the lifting sequence of crawl gait.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2012.05a
• /
• pp.307-308
• /
• 2012

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.107-119
• /
• 2023

The technology that recognizes a soldier's motion and movement status has recently attracted large attention as a combination of wearable technology and artificial intelligence, which is expected to upend the paradigm of troop management. The accuracy of state determination should be maintained at a high-end level to make sure of the expected vital functions both in a training situation; an evaluation and solution provision for each individual's motion, and in a combat situation; overall enhancement in managing troops. However, when input data is given as a timer series or sequence, existing feedforward networks would show overt limitations in maximizing classification performance. Since human behavior data (3-axis accelerations and 3-axis angular velocities) handled for military motion recognition requires the process of analyzing its time-dependent characteristics, this study proposes a high-performance data-driven classifier which utilizes the long-short term memory to identify the order dependence of acquired data, learning to classify eight representative military operations (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). Since the accuracy is highly dependent on a network's learning conditions and variables, manual adjustment may neither be cost-effective nor guarantee optimal results during learning. Therefore, in this study, we optimized hyperparameters using Bayesian optimization for maximized generalization performance. As a result, the final architecture could reduce the error rate by 62.56% compared to the existing network with a similar number of learnable parameters, with the final accuracy of 98.39% for various military operations.

• Journal of Intelligence and Information Systems
• /
• v.29 no.2
• /
• pp.23-34
• /
• 2023

Wearable technology for military applications has received considerable attention as a means of personal status check and monitoring. Among many, an implementation to recognize specific motion states of a human is promising in that allows active management of troops by immediately collecting the operational status and movement status of individual soldiers. In this study, as an extension of military wearable application research, a new ankle wearable device is proposed that can glean the information of a soldier on the battlefield on which action he/she takes in which environment. Presuming a virtual situation, the soldier's upper limbs are easily exposed to uncertainties about circumstances. Therefore, a sensing module is attached to the ankle of the soldier that may always interact with the ground. The obtained data comprises 3-axis accelerations and 3-axis rotational velocities, which cannot be interpreted by hand-made algorithms. In this study, to discern the behavioral characteristics of a human using these dynamic data, a data-driven model is introduced; four features extracted from sliced data (minimum, maximum, mean, and standard deviation) are utilized as an input of the model to learn and classify eight primary military movements (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). As a result, the proposed device could recognize a movement status of a solider with 95.16% accuracy in an arbitrary test situation. This research is meaningful since an effective way of motion recognition has been introduced that can be furtherly extended to various military applications by incorporating wearable technology and artificial intelligence.